{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T17:16:12Z","timestamp":1791998172828,"version":"4.4.0"},"reference-count":21,"publisher":"Elsevier BV","issue":"2","license":[{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/100006374","name":"David O. McKay School of Education, Brigham Young University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","thekneejournal.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["The Knee"],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1016\/j.knee.2019.11.020","type":"journal-article","created":{"date-parts":[[2019,12,25]],"date-time":"2019-12-25T23:26:20Z","timestamp":1577316380000},"page":"535-542","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":76,"title":["Automated detection &amp; classification of knee arthroplasty using deep learning"],"prefix":"10.1016","volume":"27","author":[{"given":"Paul H.","family":"Yi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinchi","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tae Kyung","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haris I.","family":"Sair","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ferdinand K.","family":"Hui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory D.","family":"Hager","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Fritz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julius K.","family":"Oni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.knee.2019.11.020_bb0005","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1016\/j.jacr.2017.12.037","article-title":"Artificial intelligence and radiology: collaboration is key","author":"Yi","year":"2018","journal-title":"J Am Coll Radiol"},{"key":"10.1016\/j.knee.2019.11.020_bb0010","article-title":"Performance of a deep-learning neural network model in assessing skeletal maturity on pediatric hand radiographs","author":"Larson","year":"2017","journal-title":"Radiology"},{"key":"10.1016\/j.knee.2019.11.020_bb0015","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","article-title":"A survey on deep learning in medical image analysis","volume":"42","author":"Litjens","year":"2017","journal-title":"Med Image Anal"},{"key":"10.1016\/j.knee.2019.11.020_bb0020","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1016\/j.crad.2017.11.015","article-title":"Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks","volume":"73","author":"Kim","year":"2018","journal-title":"Clin Radiol"},{"key":"10.1016\/j.knee.2019.11.020_bb0025","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1080\/17453674.2017.1344459","article-title":"Artificial intelligence for analyzing orthopedic trauma radiographs","volume":"88","author":"Olczak","year":"2017","journal-title":"Acta Orthop"},{"key":"10.1016\/j.knee.2019.11.020_bb0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.arth.2018.02.067","article-title":"Artificial intelligence, machine learning, deep learning, and cognitive computing: what Do these terms mean and how will they impact health care?","author":"Bini","year":"2018","journal-title":"J Arthroplasty"},{"key":"10.1016\/j.knee.2019.11.020_bb0035","doi-asserted-by":"crossref","first-page":"2211","DOI":"10.1001\/jama.2017.18152","article-title":"development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes","volume":"318","author":"Ting","year":"2017","journal-title":"JAMA"},{"key":"10.1016\/j.knee.2019.11.020_bb0040","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1038\/nature21056","article-title":"Dermatologist-level classification of skin cancer with deep neural networks","volume":"542","author":"Esteva","year":"2017","journal-title":"Nature"},{"key":"10.1016\/j.knee.2019.11.020_bb0045","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1148\/radiol.2017162326","article-title":"Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks","volume":"284","author":"Lakhani","year":"2017","journal-title":"Radiology"},{"key":"10.1016\/j.knee.2019.11.020_bb0050","first-page":"196","article-title":"National projections of time, cost and failure in implantable device identification: Consideration of unique device identification use. Healthc (Amsterdam, Netherlands)","volume":"3","author":"Wilson","year":"2015"},{"key":"10.1016\/j.knee.2019.11.020_bb0055","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.arth.2013.06.027","article-title":"Revision total hip and knee arthroplasty implant identification: implications for use of unique device identification 2012 AAHKS member survey results","volume":"29","author":"Wilson","year":"2014","journal-title":"J Arthroplasty"},{"key":"10.1016\/j.knee.2019.11.020_bb0060","series-title":"Ortho Atlas \u2013 hip arthroplasty \u2013 U.S. femoral implants 1938\u20132008","author":"Branovacki","year":"2008"},{"key":"10.1016\/j.knee.2019.11.020_bb0065","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"10.1016\/j.knee.2019.11.020_bb0070","article-title":"ImageNet large scale visual recognition","author":"Russakovsky","year":"2014","journal-title":"ArXiv;"},{"key":"10.1016\/j.knee.2019.11.020_bb0075","series-title":"Deep residual learning for image recognition","author":"He","year":"2015"},{"key":"10.1016\/j.knee.2019.11.020_bb0080","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1007\/s10278-017-9980-7","article-title":"Deep convolutional neural networks for endotracheal tube position and X-ray image classification: challenges and opportunities","volume":"30","author":"Lakhani","year":"2017","journal-title":"J Digit Imaging"},{"key":"10.1016\/j.knee.2019.11.020_bb0085","series-title":"Learning deep features for discriminative localization","first-page":"2921","author":"Zhou","year":"2015"},{"key":"10.1016\/j.knee.2019.11.020_bb0090","doi-asserted-by":"crossref","first-page":"923","DOI":"10.1148\/radiol.2017162664","article-title":"Automated critical test findings identification and online notification system using artificial intelligence in imaging","volume":"285","author":"Prevedello","year":"2017","journal-title":"Radiology"},{"key":"10.1016\/j.knee.2019.11.020_bb0095","series-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2015"},{"key":"10.1016\/j.knee.2019.11.020_bb0100","article-title":"A deep-learning system for fully-automated peripherally inserted central catheter (PICC) tip detection","author":"Lee","year":"2017","journal-title":"J Digit Imaging"},{"key":"10.1016\/j.knee.2019.11.020_bb0105","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-018-34164-6","article-title":"MRI compatibility: automatic brain shunt valve recognition using feature engineering and deep convolutional neural networks","volume":"8","author":"Giancardo","year":"2018","journal-title":"Sci Rep"}],"container-title":["The Knee"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0968016019303102?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0968016019303102?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,18]],"date-time":"2025-10-18T21:50:20Z","timestamp":1760824220000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0968016019303102"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3]]},"references-count":21,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["S0968016019303102"],"URL":"https:\/\/doi.org\/10.1016\/j.knee.2019.11.020","relation":{},"ISSN":["0968-0160"],"issn-type":[{"value":"0968-0160","type":"print"}],"subject":[],"published":{"date-parts":[[2020,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Automated detection & classification of knee arthroplasty using deep learning","name":"articletitle","label":"Article Title"},{"value":"The Knee","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knee.2019.11.020","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2019 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}